Dan Cayan Scripps Institution of Oceanography, Climate Research Division, UCSD and Water Resources Division, USGS Thanks: Mike Dettinger, Noah Knowles, Mary Tyree California’s Future Climate Lessons from Scenarios Assessments Funding: PIER Program, California Energy Commission RISA Program, NOAA Office of Global Programs DOE More info: http//:meteora . ucsd . edu/CAP /
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Dan Cayan Scripps Institution of Oceanography, Climate Research Division, UCSD and Water Resources Division, USGS Thanks: Mike Dettinger, Noah Knowles,
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Dan Cayan Scripps Institution of Oceanography, Climate Research Division, UCSD
andWater Resources Division, USGS
Thanks: Mike Dettinger, Noah Knowles, Mary Tyree
California’s Future ClimateLessons from Scenarios Assessments
Funding: PIER Program, California Energy Commission RISA Program, NOAA Office of Global Programs DOE
temperatures temperatures just below just below freezing?freezing?
““Rain vs Snow”Rain vs Snow”
More vulnerableMore vulnerable
YOSEMITE
Computed by Mike Dettinger from gridded Computed by Mike Dettinger from gridded historical US weather data (from Bates et al, in historical US weather data (from Bates et al, in
rev)rev)
Less vulnerableLess vulnerable
Winter (Nov-Mar) SFE/P trends at western USweather stations: symbol area is proportional to study-period changes, measured in standard deviations as indicated; circles indicate high trend significance (p<0.05), squares indicate lower trend significance (p>0.05).
More RainLess SnowWY 1949-2004
Noah Knowles et al. 2006 in press J. Climate
We face significant losses of spring snowpack
By the end of the century California could lose half of its late spring snow pack due to climate warming. This simulation by Noah Knowles is guided by temperature changes from PCM’s Business-as-usual climate simulation. (a middle of the road emissions scenario)
• Less snow, more rain
• Particularly at lower elevations
• Earlier run-off
• More floods
• Less stored water
Knowles and Cayan 2001
since 1985 the number of large wildfires in western U.S. increased by 4X
Anthony Westerling et al. Science August 2006
Large wildfire
threat isaggravated by warmer
springs and summers
Anthony Westerling et al. Science August 2006
Ocean Beach , February 1983
Extreme storm-forced sea levels during an extreme tide
Observed SFO (left) and modeled Global (right). Sea level rise estimates based upon an envelope of output from several GHG emission scenarios
observed
Projected envelope of global s.l. rise
Climate models Only provide loose guidance onThe amount of sea level rise, butIt is very likely that rates will increase
San Francisco Bay/Delta Water Levels Confluence of sea level rise and increased flooding
Climate models project 1.5-2.C ocean surface warming by end–of-century.
Greater warming on land than oceans would amplify California coast-interior thermal gradient.
Summer land warming is accentuated
GFDL CM2.1 Jun-Aug air temp change2070-2099 minus 1961-1990
GFDL CM2.1 is a medium-high sensitivity model. Other models produce less (or more) warming
Modeling climate over California’s complex terrain: July 10m Wind Diurnal Variation
Hist means (inches):Div2 36.02Gfdl 43.13Pcm 29.63
Are modelscapable of producing realisticsuite of
wet and dryspells?
Distribution ofObs and simulated
5yr precip departures
obs
sim
sim
Sacramento drainage div
California needs a sustained modern Climate Observation Network
Douglas AldenScripps Institution of OceanographyInstalling met stationLee Vining, CA
Implications for Monitoring Primary snowpack loss is above ~1500m
Knowles and Cayan, 2004
Total number of stream gages below 1500m
(red)
Total number of HCDN gages below
1500m (red)
Total number of gages above 1500m (blue)
Total number of HCDN gages above
1500m (blue)
Rain-snow transition zoneNeeds more
Careful monitoing
Over all Stream gages, present-day elevational bias is small…
…but climate-quality HCDN subset is under-represented in crucial elevations.
Noah Knowles, USGS)
……on the other hand, it can be very weton the other hand, it can be very wetMay 16th 2005 A warm storm in the SierraMay 16th 2005 A warm storm in the Sierra Yosemite Valley floods from a 1” rainYosemite Valley floods from a 1” rain
need to understand event scale phenomena projected heat wave days
SRES A2 GHG Emissions Scenario
Slide 11Slide 11
Need observations of 3-d, upstream atmosphere
Hydromet testbed, NOAA ETL and collaborators
How to effectively work and learn across disciplines?
Scenarios, not forecasts
PCM. GFDL, HADModel-based
Climate Projections
Agriculture
Water Energy
Forests/Fire
Coping Capacity/Preparedness
Impacts-Physical-Ecological-Economic-Social
HumanHealth
Coasts
Susi Moser, NCAR
Recommendations (without much discussion) :Improved, sustained observations
higher spatial resolution, more coverage
3-d atmosphere and ocean upstream
California meso-micro climates including urban and agricultural settings
improve insitu network, real-time communications
scientific quality record keeping of economic, social measures
data archeology
Continued modeling at several scales, disciplinesOngoing climate simulation compute consortium Ongoing Consortium for
climate simulation/prediction to knit state/campuses/labs
End-to-end assessments, including eco, economic, social; close State participation
Study extreme events as well as secular changes
Study aerosol-clouds-precipitation
Link with other regional, national, international efforts
Support California State Climate Scenarios Assessments
Promote CEC-PIER Annual Climate Change Conference
Develop closer, better links to decision makers; strengthen outreach
Fellowship program for grad students, post docs to ensure continuity, new generation